Low velocity layer characterization in the Niger Delta: Implications for seismic reflection data quality

2017 ◽  
Vol 90 (2) ◽  
pp. 187-195
Author(s):  
A. I. Opara ◽  
C. C. Agoha ◽  
C. N. Okereke ◽  
U. P. Adiela ◽  
C. N. Onwubuariri ◽  
...  
Keyword(s):  
Data Quality ◽  
Niger Delta ◽  
Seismic Reflection ◽  
Low Velocity ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Low Velocity Layer ◽  
Velocity Layer

An example of extreme near-surface variability in shallow seismic reflection data

2016 ◽  
Vol 4 (3) ◽  
pp. SH1-SH9
Author(s):  
Steven D. Sloan ◽  
J. Tyler Schwenk ◽  
Robert H. Stevens
Keyword(s):  
Seismic Reflection ◽  
Field Data ◽  
Low Velocity ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Shallow Subsurface ◽  
Reflection Data ◽  
Shallow Seismic ◽  
Low Velocity Layer ◽  
Velocity Layer

Variability of material properties in the shallow subsurface presents challenges for near-surface geophysical methods and exploration-scale applications. As the depth of investigation decreases, denser sampling is required, especially of the near offsets, to accurately characterize the shallow subsurface. We have developed a field data example using high-resolution shallow seismic reflection data to demonstrate how quickly near-surface properties can change over short distances and the effects on field data and processed sections. The addition of a relatively thin, 20 cm thick, low-velocity layer can lead to masked reflections and an inability to map shallow reflectors. Short receiver intervals, on the order of 10 cm, were necessary to identify the cause of the diminished data quality and would have gone unknown using larger, more conventional station spacing. Combined analysis of first arrivals, surface waves, and reflections aided in determining the effects and extent of a low-velocity layer that inhibited the identification and constructive stacking of the reflection from a shallow water table using normal-moveout-based processing methods. Our results also highlight the benefits of using unprocessed gathers to pragmatically guide processing and interpretation of seismic data.

Application of waveform tomography to marine seismic reflection data from the Queen Charlotte Basin of western Canada

Geophysics ◽  
2011 ◽  
Vol 76 (2) ◽  
pp. B55-B70 ◽  
Author(s):  
E. M. Takam Takougang ◽  
A. J. Calvert
Keyword(s):  
Seismic Reflection ◽  
Field Data ◽  
Velocity Model ◽  
P Wave ◽  
Low Velocity ◽  
Seismic Line ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Sonic Log ◽  
Waveform Tomography

To obtain a higher resolution quantitative P-wave velocity model, 2D waveform tomography was applied to seismic reflection data from the Queen Charlotte sedimentary basin off the west coast of Canada. The forward modeling and inversion were implemented in the frequency domain using the visco-acoustic wave equation. Field data preconditioning consisted of f-k filtering, 2D amplitude scaling, shot-to-shot amplitude balancing, and time windowing. The field data were inverted between 7 and 13.66 Hz, with attenuation introduced for frequencies ≥ 10.5 Hz to improve the final velocity model; two different approaches to sampling the frequencies were evaluated. The limited maximum offset of the marine data (3770 m) and the relatively high starting frequency (7 Hz) were the main challenges encountered during the inversion. An inversion strategy that successively recovered shallow-to-deep structures was designed to mitigate these issues. The inclusion of later arrivals in the waveform tomography resulted in a velocity model that extends to a depth of approximately 1200 m, twice the maximum depth of ray coverage in the ray-based tomography. Overall, there is a good agreement between the velocity model and a sonic log from a well on the seismic line, as well as between modeled shot gathers and field data. Anomalous zones of low velocity in the model correspond to previously identified faults or their upward continuation into the shallow Pliocene section where they are not readily identifiable in the conventional migration.

An indirect seismic method for determining the thickness of a low‐velocity layer underlying a high‐velocity layer

Geophysics ◽  
1981 ◽  
Vol 46 (7) ◽  
pp. 1003-1008 ◽  
Author(s):  
K. L. Kaila ◽  
H. C. Tewari ◽  
V. G. Krishna
Keyword(s):  
High Velocity ◽  
Low Velocity ◽  
Field Case ◽  
Reflection Data ◽  
First Arrival ◽  
Low Velocity Layer ◽  
Velocity Of Propagation ◽  
High Velocity Layer ◽  
Refraction Data ◽  
Velocity Layer

We present an indirect method for determining the thickness of a low‐velocity layer (LVL) underlying a high‐velocity layer (HVL) in seismic prospecting. Comparison of the average velocity‐depth function determined from the first arrival refraction data with that obtained from reflection data in the same region, especially below the LVL, makes it possible to recognize the presence of the LVL and to estimate its probable thickness. The applicability of the method has been demonstrated in a field case where the presence of an LVL is indicated by geologic evidence. It has been shown that thickness estimates of an LVL and an HVL can be made reliably in situations where the velocity in the LVL can be accurately estimated from nearby exposures or in a drilled well. For the field case analyzed, a thickness of 0.75 km was estimated for an LVL (probably Mesozoic sediments) underlying a 0.25 km thick HVL (probably basalt). The velocity of propagation in the LVL was taken from seismic data on nearby exposed Mesozoics as 4.0 km/sec, and the velocity of the HVL is 5.4 km/sec, based on the refraction data. In areas where the velocity in the LVL cannot be inferred accurately, an upper limit of this velocity can be obtained which permits estimation of the maximum possible thickness of the LVL. In the field example presented, we show that the velocity in the LVL cannot exceed 4.17 km/sec.

Modeling and processing of scattered waves in seismic reflection surveys

Geophysics ◽  
1988 ◽  
Vol 53 (4) ◽  
pp. 466-478 ◽  
Author(s):  
Bruce S. Gibson ◽  
Alan R. Levander
Keyword(s):  
Surface Waves ◽  
Seismic Reflection ◽  
Wave Scattering ◽  
Body Wave ◽  
Simple Relation ◽  
Velocity Variation ◽  
Low Velocity ◽  
Spectral Character ◽  
Seismic Reflection Data ◽  
Reflection Data

Various wave‐scattering mechanisms are known to degrade reflection signals by producing noise in seismic reflection data. Synthetic 2-D acoustic‐wave finite‐ difference data sets illustrate the effects of two such mechanisms. Twenty‐five shot gathers were generated for each of two models and the data were processed as standard CMP surveys. In one model, an irregular low‐ velocity surface layer produced multiply scattered surface waves that appear as linear noise trains in common‐shot gathers and stacked sections. The scattering of upcoming reflections at the lower interface of the layer also produced a significant amount of noise. When predictive deconvolution was applied before stack to reduce reverberations, the spectral character of the scattered surface waves seriously inhibited the action of that process. In the second model, a zone of smooth, random velocity variation was imposed between two reflectors deeper in the model. The heterogeneous zone (±5 percent rms velocity variation) substantially degraded the signal reflected from below it; events produced by body‐wave scattering are characterized by higher phase velocities than those seen in the first model. Conventional CMP stacking produced discontinuous subhorizontal events from the disturbed zone. The limited bandwidth of the propagating signal and spatial filtering attributable to CMP stacking cause these events to bear no simple relation to the velocity anomalies of the model, even after migration.

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